Transporters as Targets for Drugs

4 Topics in Medicinal Chemistry Editorial Board: P. R. Bernstein · A. Buschauer · G. J. Georg · J. A. Lowe · H. U. Stilz

Transporters as Targets for Drugs Volume Editors: Susan Napier · Matilda Bingham With contributions by M. D. Andrews · G. Antoni · M. Bingham · R. J. Bridges A. D. Brown · Z. Chen · S. G. Dahl · P. V. Fish · R. Gilfillan H. Hall · J. L. Katz · J. Kerr · S. Napier · A. Hauck Newman S. A. Patel · A. W. Ravna · G. Sager · P. Skolnick · J. Sörensen A. Stobie · I. Sylte · F. Wakenhut · G. Walker · G. A. Whitlock G. Wishart · J. Yang 123

Drug research requires interdisciplinary team-work at the interface between chemistry, biology and medicine. Therefore, the new topic-related series should cover all relevant aspects of drug research, e.g. pathobiochemistry of diseases, identification and validation of (emerging) drug targets, structural biology, drugability of targets, drug design approaches, chemogenomics, synthetic chemistry including combinatorial methods, bioorganic chemistry, natural compounds, high-throughput screening, pharmacological in vitro and in vivo investigations, drug-receptor interactions on the molecular level, structure-activity relationships, drug absorption, distribution, metabolism, elimination, toxicology and pharmacogenomics. In references Topics in Medicinal Chemistry is abbreviated Top Med Chem and is cited as a journal. Springer WWW home page: springer.com Visit the TIMC content at springerlink.com ISSN 1862-2461 e-ISSN 1862-247X ISBN 978-3-540-87911-4 e-ISBN 978-3-540-87912-1 DOI 10.1007/978-3-540-87912-1 Springer Dordrecht Heidelberg London New York Library of Congress Control Number: 2009926137
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Volume Editors Dr. Susan Napier Schering Plough Corporation Newhouse, Motherwell, ML1 5SH United Kingdom [email protected] Dr. Matilda Bingham Schering Plough Corporation Newhouse, Motherwell, ML1 5SH United Kingdom [email protected] Editorial Board Dr. Peter R. Bernstein AstraZeneca Pharmaceuticals 1800 Concord Pike Fairfax Research Center B313 PO Box 15437 Wilmington, DE 19850-5437 USA Prof. Dr. Armin Buschauer Institute of Pharmacy University of Regensburg Universitätsstr. 31 93053 Regensburg Germany Prof. Dr. Gunda J. Georg University of Minnesota Department of Medical Chemistry 8-101A Weaver Densford Hall Minneapolis, MN 55455 USA John A. Lowe [email protected] Dr. Hans Ulrich Stilz Aventis Pharma Deutschland GmbH Geb. G 838 65926 Frankfurt a.M. Germany

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Preface to the Series Medicinalchemistryisbothscienceandart.Thescienceofmedicinalchemistry offers mankind one of its best hopes for improving the quality of life. The art of medicinal chemistry continues to challenge its practitioners with the need for both intuition and experience to discover new drugs. Hence sharing the experience of drug discovery is uniquely beneficial to the field of medicinal chemistry. The series Topics in Medicinal Chemistry is designed to help both novice and experienced medicinal chemists share insights from the drug discovery process. For the novice, the introductory chapter to each volume provides background and valuable perspective on a field of medicinal chemistry not available elsewhere. Succeeding chapters then provide examples of successful drug discovery efforts that describe the most up-to-date work from this field. The editors have chosen topics from both important therapeutic areas and from work that advances the discipline of medicinal chemistry. For example, cancer, metabolic syndrome and Alzheimer’s disease are fields in which academia and industry are heavily invested to discover new drugs because of their considerable unmet medical need. The editors have therefore prioritized covering new developments in medicinal chemistry in these fields. In addition, important advances in the discipline, such as fragment-based drug design and other aspects of new lead-seeking approaches, are also planned for early volumes in this series. Each volume thus offers a unique opportunity to capture the most up-to-date perspective in an area of medicinal chemistry. Dr. Peter R. Bernstein Prof. Dr. Armin Buschauer Prof. Dr. Gunda J. Georg Dr. John Lowe Dr. Hans Ulrich Stilz

Preface to Volume 4 Transporters are proteins which span the plasma membrane and regulate the traffic of small molecules in and out of the cell. Transporters play a particularly important role in chemical signalling between neurons in the CNS, where they act to control the concentration of neurotransmitters in the synapse. The majority of transporters which are actively being pursued as targets for drug discovery are CNS located and this reflects the history of the field which began with the tricyclic antidepressants (TCAs) over half a century ago. The use of transporter inhibition to regulate the synaptic concentrations of key neurotransmitters is an established approach in the discovery of psychiatric medications. This volume reviews advances in the field of transporters as targets for drug discovery in the last 10 years. The volume will be of interest to scientists engaged in drug research in the pharmaceutical industry, biotech and academia. Following an overview chapter, seven chapters written by leading experts in their area reflect a range of topics pertinent to the transporter field. General topics include recent advances in the structural biology of transporters and its impact on potential structure-based drug design and the design of ligands for Positron Emission Tomography and the importance of molecular imaging in understanding early clinical data. Medicinal chemistry approaches are described outlining the discovery of selective serotonin, noradrenaline and dopamine reuptake inhibitors, current efforts towards the discovery of mixed re-uptake inhibitors with varied “flavours” of monoamine inhibition, advances in the development of inhibitors for the glycine transporter and the discovery of subtype selective EAAT inhibitors. In addition to being an interesting read, the reader will receive a critical overview of progress made in this rapidly developing field. January 2009 Matilda Bingham Susan Napier

Contents Overview: Transporters as Targets for Drug Discovery M. Bingham · S. Napier . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Membrane Transporters: Structure, Function and Targets for Drug Design A. W. Ravna · G. Sager · S. G. Dahl · I. Sylte . . . . . . . . . . . . . . . . 15 Design of Monoamine Reuptake Inhibitors: SSRIs, SNRIs and NRIs G. A. Whitlock · M. D. Andrews · A. D. Brown · P. V. Fish A. Stobie · F. Wakenhut . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 Atypical Dopamine Uptake Inhibitors that Provide Clues About Cocaine’s Mechanism at the Dopamine Transporter A. Hauck Newman · J. L. Katz . . . . . . . . . . . . . . . . . . . . . . . 95 The Design, Synthesis and Structure–Activity Relationship of Mixed Serotonin, Norepinephrine and Dopamine Uptake Inhibitors Z. Chen · J. Yang · P. Skolnick . . . . . . . . . . . . . . . . . . . . . . . . 131 Molecular Imaging of Transporters with Positron Emission Tomography G. Antoni · J. Sörensen · H. Hall . . . . . . . . . . . . . . . . . . . . . . 155 Pharmacology of Glutamate Transport in the CNS: Substrates and Inhibitors of Excitatory Amino Acid Transporters (EAATs) and the Glutamate/Cystine Exchanger System x – c R. J. Bridges · S. A. Patel . . . . . . . . . . . . . . . . . . . . . . . . . . 187 Glycine Transporters and Their Inhibitors R. Gilfillan · J. Kerr · G. Walker · G. Wishart . . . . . . . . . . . . . . . . 223 Subject Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 249

Top Med Chem (2009) 4: 1–13 DOI 10.1007/7355_2009_029  Springer-Verlag Berlin Heidelberg Published online: 28 March 2009 Overview: Transporters as Targets for Drug Discovery Matilda Bingham (✉) · Susan Napier Schering Plough Corporation, Newhouse, Motherwell ML1 5SH, UK [email protected] 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 2 Transporter Classification . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 2.1 The ATP Binding Cassette Family . . . . . . . . . . . . . . . . . . . . . . . 2 2.2 The Solute Carrier Family . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 2.2.1 The Major Facilitator Superfamily . . . . . . . . . . . . . . . . . . . . . . . 3 2.2.2 The Neurotransmitter: Sodium Symporter Family . . . . . . . . . . . . . . 3 2.2.3 The Dicarboxylate/Amino Acid:Cation (Na+ or H+ ) Symporter (DAACS) Family . . . . . . . . . . . . . . . . . . . . . . . . . . 5 3 NSS Transporter Assays . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 4 Transporters and Structure-Based Drug Design (SBDD) . . . . . . . . . . 6 5 Transporters as Targets for Drug Discovery . . . . . . . . . . . . . . . . . 8 6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 Abbreviations ABC ATP binding cassette ADHD Attention deficit hyperactivity disorder ATP Adenosine triphosphate DAACS Dicarboxlate/amino acid:cation (Na+ or H+ ) symporter DAT Dopamine reuptake transporter EAAT Excitatory amino acid transporter GLUT Glucose transporter HTS High-throughput screening PET Positron emission tomography P-gp P-glycoprotein MDD Major depressive disorder MFS Major facilitator superfamily NET Noradrenaline reuptake transporter NRI Noradrenaline reuptake inhibitor NSS Neurotransmitter; sodium symporter SBDD Structure-based drug design SERT Serotonin reuptake transporter SNRI Serotonin noradrenaline inhibitor SSRI Selective serotonin reuptake inhibitor TCA Tricyclic antidepressant

2 M. Bingham · S. Napier 1 Introduction Transporters are proteins that span the plasma membrane and regulate the traffic of small molecules in and out of the cell. They play a particularly important role in chemical signalling between neurons in the CNS, where they act to control the concentration of neurotransmitters in the synapse. In most systems the termination of chemical transmission is achieved by rapid uptake of the transmitter molecule from the synapse by transporters located on the synaptic terminal or surrounding glial cells. Another key role for transporters is in excluding undesirable xenobiotics from the cell, whilst allowing key molecules required for the cell life cycle to enter. It is increasingly recognised that these efflux or uptake transporters respectively, play an important role in the disposition of many marketed drugs, and whilst the field of drug transport is yet to attain the level of maturity of drug metabolism, it is certain to be of increasing importance in future drug discovery programmes. 2 Transporter Classification Transporters can be classed into two main families; the ATP binding cassette (ABC) family, and the solute carrier (SLC) family. The SLC family is a very broad categorisation which encompasses, amongst others, three important families of transporters for organic molecules; the major facilitator superfamily (MFS) and two neurotransmitter transporter families, the neurotransmitter; sodium symporter (NSS, or SLC6) and the dicarboxylate/amino acid:cation (Na+ or H+ ) symporter (DAACS, or SLC1) family. 2.1 The ATP Binding Cassette Family The ATP binding cassette (ABC) family use a primary active transport mechanism to transport the substrate across the membrane [1, 2]. As the name suggests, the free energy stored in the phosphate bonds of ATP is harnessed directly to move substances through the membrane against a concentration gradient from a lower to a higher concentration. Perhaps the best known example of this class is the efflux transporter P-glycoprotein or P-gp, also known as MDR1 and ABCB1. This protein was identified because of its overexpression in cultured tumor cells associated with acquired resistance to multiple anticancer agents [3]. It has since been recognised that this transporter is expressed in many normal tissues including the gastrointestinal tract and blood–brain barrier and plays a key role in limiting the absorption and CNS

Overview: Transporters as Targets for Drug Discovery 3 penetration of several marketed drugs [4]. Interaction with P-gp can also have significant consequences in terms of drug–drug interactions [5]. Testing for P-gp inhibition in cell-based systems is now a routine in vitro screen incorporated into early phase drug discovery programmes. Following the discovery of P-gp a number of other transporters from the ABC family have also been shown to have important roles in the disposition of drugs including MRP2 (ABCC2) [6], SPGP (BSEP, ABCB11) [7], and BCRP (ABCG2) [8, 9]. Two transporter families from the SLC group, the organic anion transporting polypeptide (OATP or SLC21, SLCO and SLC22) family [10], and the organic cation transporter (OCT, or SLC22) family [11], are also important in the uptake of drugs into the brain and systemic circulation. 2.2 The Solute Carrier Family 2.2.1 The Major Facilitator Superfamily The major facilitator superfamily (MFS) is the largest group of transporters containing over 15, 000 sequenced members to date [12]. This family is ubiquitous in both eukaryotes and prokaryotes and accepts an enormous diversity of substrates including sugars, sugar phosphates, polyols, nucleosides, amino acids, neurotransmitters, and peptides amongst many others. The MFS proteins operate by “facilitating” the diffusion of a solute from a higher to a lower electrochemical potential, via specific binding between the solute and the transporter. The substrate of interest is therefore transported by one of three mechanisms: (a) uniport where the substrate is the “solute” and is energised solely by its own concentration gradient, (b) symport where the substrate is translocated in the same direction as the solute, and (c) antiport wherein the substrate is transported in the opposite direction to the solute. This facilitated diffusion therefore does not require a supply of energy. The potential of these proteins as targets for drug discovery is beginning to be realised; for example several companies are currently pursuing clinical trials on inhibitors of the glucose transporter SGLT-2 for the treatment of non-insulin dependent diabetes [13]. 2.2.2 The Neurotransmitter: Sodium Symporter Family The neurotransmitter: sodium symporter (NSS) family is arguably the best exploited in terms of targets for drug discovery. Many marketed drugs act on NSS transporters including blockbusters such as fluoxetine 1 (Prozac), sertraline 2 (Zoloft), paroxetine 3 (Paxil), buproprion 4 (Wellbutrin) and venlafaxine 5 (Effexor), as well as the newer duloxetine 6 (Cymbalta) and

4 M. Bingham · S. Napier Fig. 1 a number of psychostimulant drugs of abuse such as cocaine 7, and amphetamine 8 (Fig. 1) . The NSS family plays a particularly important role in neurotransmitter signalling in the CNS and hence NSS transporter inhibition has found widespread application in psychiatry. The NSS family of transporters, which includes SERT, NET, DAT, GAT and GlyT therefore forms the focus for this volume. The NSS transporters use a secondary active transport mechanism to translocate the substrate across the membrane; in an analogous fashion to the ABC family, the energy stored in ATP phosphate bonds is harnessed to drive an ion, eg. H+ or Na+ , down a concentration gradient. At the same time the substrate is transported against its concentration gradient. The process can be termed symport or antiport as the substrate is transported in the same direction, or the opposite direction to the ion current, respectively.

Overview: Transporters as Targets for Drug Discovery 5 2.2.3 The Dicarboxylate/Amino Acid:Cation (Na+ or H+ ) Symporter (DAACS) Family The most prominent members of this family are the sodium-dependent excitatory amino acid transporters EAATs which have been implicated in a number of neurodegenerative and neuropsychiatric disorders. The EAATs use a secondary active transport mechanism in which the transport of the excitatory amino acid glutamate across the membrane is accompanied by the transport of three sodium ions and a proton. 3 NSS Transporter Assays The two most common methods for evaluating transporter inhibitors in vitro are equilibrium binding assays and functional reuptake assays, reported as Kis or IC50s. It is this data which is most commonly used in medicinal chemistry programmes to compare compounds of interest and to select compounds for progression to later stage drug development. The classic methods for both approaches use a radiolabelled compound; either a radiolabelled transporter inhibitor for the binding assay, or a radiolabelled neurotransmitter for measuring the reuptake inhibition. Both binding and functional assays can be carried out in either cultured cell systems (where available) or in native tissue such as rat synaptosomes. Care needs to be taken in extrapolating data from these assays, it is not uncommon to observe potency differences between binding and functional assays and between overexpressing systems and native preparations. This is of particular importance when a mixed inhibitor profile is desired, as is increasingly the case in the monoamine transporter field (vide infra Chen et al. and Whitlock et al.). The situation is further complicated by the fact that there is significant “cross talk” between neurotransmitter neurons in the brain such that a given inhibitor profile in vitro may not correlate with the expected profile in vivo. In vivo neurochemistry studies are usually required to confirm the inhibition of the desired neurotransmitter/s in a suitable animal model. More recently, there has been progress in developing fluorescence-based functional uptake assays, notably for the monoamine transporters [14–16] GlyT [17, 18] and the EAATs [19]. This allows for the possibility of large scale high-throughput screening (HTS) campaigns. The costs associated with the use and disposal of radiolabelled compounds make the classical binding and functional assays less amenable to HTS, and hence the development of viable fluorescent substrates for other transporters is eagerly anticipated. More detailed pharmacology of transporter inhibitors can be evaluated in functional assays to look at whether the compound is a substrate, or inhibitor,

6 M. Bingham · S. Napier a reversible or non-reversible binder and to investigate inhibition kinetics. However, these assays are not routinely carried out and are typically reserved for compounds that have been selected as potential drug candidates. 4 Transporters and Structure-Based Drug Design (SBDD) Obtaining suitable crystals for X-ray structure determination is a problem common to all classes of integral membrane proteins, and transporters are no exception. The central portion of the transporter which is embedded in the plasma membrane usually exists as a bundle of α-helices which has evolved to be stabilised by a lipid environment, conversely, the extracellular and intracellular loops which link the α-helices are hydrophilic in character. This environment is very difficult to replicate in suitable crystallisation conditions, and as a result it has only been in the last decade that the first high-resolution X-ray crystal structures have started to emerge. Recently, representative transporters from each of the categories have been successfully crystallised to afford high-resolution 3D structures; three from the MFS family LacY [20], EMrD [21] and GlpT [22], the ABC importers MetNI [23], BtuCD [24, 25], HI1470/71 [26], ModBC [27], and MalFGK [28] and exporters Sav1866 [29] and MsbA [30], and two high-resolution X-ray structures from the neurotransmitter family, the NSS transporter LeuT [31] and the DAACs family archaeal glutamate transporter homologue from Pyrococcus horikoshii GltPh [32]. The availability of these structures has the potential to revolutionise our understanding of the complex kinetics and mechanisms involved in the selective recognition and transport of molecules across the plasma membrane. The potential impact of the publication of these structures on SBDD is also significant. The implications and additional potential for homology modeling, NMR studies and electron microscopy are discussed in detail by Sylte et al. (vide infra). Of particular interest, given the focus herein on the NSS transporters, is recent work from Gouaux et al. They identified the tricyclic antidepressant (TCA) clomipramine (Fig. 2) as a weak ∼ 2 µM non-competitive inhibitor of LeuT, and were able to obtain high-resolution crystal structures of clomipramine in complex with LeuT, the Leu substrate, and a sodium ion [33]. The 3D structure of LeuT, thought to share a common architecture with other NSS transporters, consists of 12 α-helical transmembrane domains, with TMs 1–5 and 6–10 related to each other by a pseudo 2-fold axis in the membrane plane (Fig. 2). The Leucine and sodium ions are bound in the centre of the protein, half way across the membrane bilayer [31]. The clomipramine bound structure shows the clomipramine positioned at the extracellular side of the transporter, just above the substrate binding pocket.

Overview: Transporters as Targets for Drug Discovery 7 Fig. 2 a Structure of Clomipramine Fig. 2 b The LeuTAa topology reported by Gouaux et al. [23], as determined by X-ray crystallography. TM1–TM5 and TM6–TM10 are related by a pseudo-two-fold axis located in the plane of the membrane. The leucine substrate is represented by a magenta triangle and the 2 sodium ions as blue circles Given that clomipramine is known to inhibit SERT and NET in humans, this clomipramine-bound structure has the potential to further our understanding of the structural basis of inhibition at the monoamine transporters. However, it is important to note that the sequences of SERT and NET are significantly different from LeuT, and recent data on SERT [34] and NET [35] suggest that the TCAs may bind in a region closer to the substrate binding pocket. A contemporaneous study by Wang and Reith et al. reported the crystal structure of LeuT in complex with the leucine substrate and the antidepressant desipramine [36]. They also reported gain-of-function mutagenesis experiments on hSERT and hDAT which suggested that the binding mode observed in the LeuT-desipramine structure is conserved in the monoamine transporters.

8 M. Bingham · S. Napier 5 Transporters as Targets for Drug Discovery This volume focusses on transporters as targets for drug discovery. A diverse range of topics are covered; from recent advances in the structural biology of transporters and its impact on potential structure-based drug design (Sylte et al.), through a case study of medicinal chemistry drug design (Newman et al.), to the design of PET ligands and their importance in understanding early clinical trial data (Antoni et al.). The monoamine transporters are the most established drug targets, and as such there are many excellent reviews covering the launched antidepressant selective serotonin uptake inhibitors (SSRIs), selective serotonin and noradrenaline reuptake inhibitors (SNRIs) and TCAs [37]. In this volume we focus rather on more recent developments in the search for second generation monoamine reuptake inhibitors which address the deficits in current marketed drugs. The SSRIs have a good side effect profile however, as antidepressants they suffer from a slow onset of action and significantly, 30–40% of patients do not respond satisfactorily to them. Conversely, although the TCAs are effective antidepressants they have poor selectivity over muscarinic, histaminic and adrenergic receptors, resulting in cardiovascular, anticholinergic and sedative side effects. Whitlock et al. describe progress in the discovery of SSRIs, noradrenaline reuptake inhibitors (NRIs), and SNRIs from 2000 to the present day. Whilst Chen et al. focus on recent developments in the search for triple SERT, NET and DAT reuptake inhibitors. The interest in these areas stems not only from the potential for improved antidepressant efficacy and side effect profiles, as has been proposed for the triple reuptake inhibitors [38], but the recognition that by tweaking the transporter profile potential therapies for other diseases associated with neurotransmitter imbalance can be developed. For example, although duloxetine 6 (Fig. 1), a dual SNRI, was initially launched in 2004 for the treatment of major depressive disorder (MDD) [39], since 2004 additional approvals have been granted for pain associated with diabetic neuropathy [40] and fibromyalgia [41], for stress urinary incontinence [42] and generalised anxiety disorder [43]. NRIs have been licensed for the treatment of attention deficit hyperactivity disorder (ADHD), as well as being of interest for the treatment of neuropathic pain. The continuing increase in the number of patents being filed for monoamine reuptake inhibitors reflects the ongoing interest in these transporters as targets for drug discovery. The monoamine reuptake transporters, and DAT in particular, are also responsible for the stimulant properties of several drugs of abuse such as cocaine and amphetamine. The mechanisms underlying the abuse potential of these drugs remain the subject of debate. The dopamine transporter (DAT) hypothesis of cocaine’s behavioral effects was first proposed by Ritz et al. [44] following their observation that there was a positive correlation between the

Overview: Transporters as Targets for Drug Discovery 9 binding affinity at DAT and the potency for self-administration of a variety of monoamine uptake inhibitors. Many studies have subsequently supported the DAT hypothesis, however it is becoming more evident that the elegant simplicity of this hypothesis may hide a more complex reality. For example, DAT knockout mice still exhibit place preference and self-administration of cocaine [45, 46]. The interdependency of the monoamine neurotransmission systems and the fact that cocaine also inhibits SERT and NET further complicate interpretation of the in vivo data. Finally, there are non-cocaine based DAT inhibitors which are used clinically which do not show abuse potential and it is one class of these inhibitors, the benztropines (Fig. 3), which forms the subject of a case study in drug discovery by Newman et al. In their chapter they review the current state-of-the-art in our understanding of the mechanisms underlying the abuse potential of this class of drugs. It is remarkable that despite nearly half a century of use of monoamine reuptake inhibitors our understanding of their mode of action, cocaine being a case in point, is still limited. Despite advances in our knowledge of the neurotransmitter systems at the molecular level, translating this information into predictions for the effect of a given compound in man is still fraught with problems. It is not possible to develop a true animal model for a disease such as MDD since it is questionable whether animals can suffer from a similar illness and we cannot ask the animal for a subjective opinion as to how it feels! This is a problem common to all psychiatric illnesses and hence the challenges associated with developing suitable animal models mean that it is often not until late stage clinical trials that the hypotheses for the therapeutic benefit of reuptake inhibition can be tested. The cost of a compound failing late in clinical development is significant and companies are increasingly looking to incorporate imaging techniques into early clinical trials for CNS drugs to limit late stage attrition rates. In their review Antoni et al. introduce the PET imaging technique and discuss the current state-of-the-art with respect to imaging the transporters. They cover not only the neurotransmitter transFig. 3

10 M. Bingham · S. Napier porters but also the ABC transporters, the glucose transporter GLUT and the vesicular monoamine transporter-2. PET imaging cannot increase the likelihood of a compound succeeding in the clinic, but rather allows companies to make faster decisions to stop the development of ineffective compounds. PET imaging can be used to relate drug pharmacokinetics in plasma to receptor occupancy, and subsequently to relate this to clinical efficacy. In the absence of the receptor occupancy information from imaging studies it is difficult to assess whether a lack of clinical efficacy is due to insufficient drug at the desired site of action or due to failure of the mechanistic hypothesis. The translatability of this non-invasive technique provides a link with PET imaging in animal models, thus allowing preclinical evaluation and ranking of new chemical entities to select the most promising to progress into the clinic. Although there are PET tracers available, there is still much work to be done to identify “ideal” PET ligands for the transporters suitable for use in the clinic. As highlighted by Antoni et al. in their review, “the stringent criteria required for a suitable PET tracer mean that the process of identifying a suitable PET ligand presents as many challenges as the discovery of a new drug”. In addition to regulating monoaminergic chemical transmission, transporters also play a role in controlling synaptic concentrations of amino acid neurotransmitters. Two such transporters for the CNS active amino acid glycine, GlyT1 and GlyT2 from the NSS family were identified in the early 1990s [47–49]. Since that time there has been significant interest in GlyT1 inhibition as a therapy for schizophrenia with the proposed additional benefit of improved cognition. Although there is substantial pharmacological evidence to support this therapeutic hypothesis, clinical proof of concept is yet to be determined. However, a number of interesting compounds have now progressed to clinical trials and hence the validity of GlyT1 as a target for schizophrenia, as well as differentiation between the different structural classes of inhibitors, is likely to be clarified in the next decade. In their review Walker et al. (vide infra) review the current medicinal chemistry landscape for the glycine transporters and report progress towards the identification of subtype selective GlyT inhibitors. Particular emphasis is given to developments in the last 2 years towards the identification of non-amino acid based inhibitors. A volume on neurotransmitter transporters would not be complete without inclusion of the EAATs. Glutamate is now recognised as the primary excitatory neurotransmitter in the CNS where glutamate synapses mediate the majority of fast excitatory neurotransmission. The glutamatergic synapses are essential for normal development and are involved in synaptic plasticity, learning and memory. Attention has tended to focus on the ionotrophic and metabotrophic glutamate receptors (iGluRs and mGluRs, respectively) as targets for therapy however, the EAATs also play an important physiological role in glutamate neurotransmission by clearing glutamate from the

Overview: Transporters as Targets for Drug Discovery 11 synapse. Bridges et al. describe recent research towards the development of subtype selective EAAT inhibitors and subsequent attempts to better understand the contributions of the different EAAT transporters. The studies to date highlight the neuroprotective role of the EAATs and point towards the use of compounds which enhance glutamate uptake for therapy. The feasibility of this as an approach is yet to be determined, since there is little precedent for developing agents which act as positive modulators of the transporters. 6 Summary The majority of transporters that are actively being pursued as targets for drug discovery are CNS located, and this probably reflects the history of the field which began with the TCAs over half a century ago. The use of transporter inhibition to regulate the synaptic concentrations of key neurotransmitters is an established approach in the discovery of psychiatric medications and the continued interest in the area is manifest in current efforts towards the discovery of mixed reuptake inhibitors with varied ‘flavours’ of monoamine inhibition. As highlighted by Whitlock et al. in their review of SNRIs, targeting multiple receptors poses significant challenges for the medicinal chemist and also complicates the biological evaluation of these novel ligands. Advances in PET ligand development (Antoni et al.), may help differentiate these second generation antidepressants in the clinic, especially if a suitable NET ligand is identified in the near future. Until recently, discovery of new inhibitors has typically been through screening compounds prioritised via a pharmacophore-rational design based approach. However, advances in assay technologies such as the development of fluorescence-based reuptake assays, and the recently published X-ray crystal structures of transporters suggest that the impact of HTS and SBDD may change the way that medicinal chemists approach the discovery of transporter inhibitors in the future. References 1. Linton KJ (2007) Physiology 22:122 2. Davidson AL, Maloney PC (2007) Trends Microbiol 15:448 3. Juliano RL, Ling V (1976) Biochim Biophys Acta 455:152 4. Sz´akacs G, V´aradi A, Özvegy-Laczka C, Sarkadi B (2008) Drug Discov Today 13:379 5. Yu DK (1999) J Clin Pharmacol 39:1203 6. Keppler D, König J, Büchler M (1997) Adv Enzym Regul 37:321 7. Childs S, Yeh RL, Georges E, Ling V (1995) Cancer Res 55:2029 8. Doyle L, Yang W, Abruzzo L, Krogmann T, Gao Y, Rishi AK, Ross DD (1998) Proc Natl Acad Sci USA 95:15665

12 M. Bingham · S. Napier 9. Miyake K, Mickley L, Litman T, Zhan Z, Robey R, Cristensen B, Brangi M, Greenberger L, Dean M, Fojo T, Bates SE (1999) Cancer Res 59:8 10. Rizwan AN, Burckhardt G (2007) Pharmaceut Res 24:450 11. Choi M-K, Song I-S (2008) Drug Metab Pharmacokin 23:243 12. Law CJ, Maloney PC, Wang D-N (2008) Annu Rev Microbiol 62:289 13. www.Thomson-pharma.com 14. Haunso A, Buchanan D (2007) J Biomol Screen 12:378 15. Mason JN, Farmar H, Tomlinson ID, Schwartz JW, Savchenko V, DeFelice LJ, Rosenthal SJ, Blakely RD (2005) J Neurosci Methods 143:3 16. Jørgensen S, Østergaard N, Peters D, Dyhring T (2008) 169:168 17. Allan L, Leith JL, Papakosta M, Morrow JA, Irving NG, McFerran BW, Clark AG (2006) Comb Chem High Throughput Screen 9:9 18. Benjamin ER, Skelton J, Hanway D, Olanrewaju S, Pruthi F, Ilyin VI, Lavery D, Victory SF, Valenzano KJ (2005) J Biomol Screen 10:365 19. Jensen AA, Brauner-Osborne H (2004) Biochem Pharmacol 67:2115 20. Abramson J, Smirnova I, Kasho V, Verner G, Kaback HR, Iwata S (2003) 301:610 21. Yin Y, He X, Szewczyk P, Nguyen T, Chang G (2006) Science 312:714 22. Huang Y, Lemieux MJ, Song J, Auer M, Wang D-N (2003) Science 301:616 23. Kadaba NS, Kaiser JT, Johnson E, Lee A, Rees DC (2008) Science 321:250 24. Locher KP, Lee AT, Rees DC (2002) Science 296:1091 25. Hvorup RN, Goetz BA, Niederer M, Hollenstein K, Perozo E, Locher KP (2007) Science 317:1387 26. Pinkett HW, Lee AT, Lum P, Locher KP, Rees DC (2007) Science 315:373 27. Hollenstein K, Frei DC, Locher KP (2007) Nature 446:213 28. Oldham ML, Khare D, Quiocho FA, Davidson AL, Chen J (2007) Nature 450:515 29. Dawson RJP, Locher KP (2006) Nature 443:180 30. Ward A, Reyes CL, Yu J, Roth CB, Chang G (2007) Proc Natl Acad Sci USA 104:19005 31. Yamashita A, Singh SK, Kuwate T, Jin Y, Gouaux E (2005) Nature 437:215 32. Yernool D, Boudker O, Jin Y, Gouaux E (2004) Nature 431:811 33. Singh SK, Yamashita A, Gouaux E (2007) Nature 448:952 34. Henry LK, Field JR, Adkins EM, Parnas ML, Vaughan RA, Zou M-F, Newman AH, Blakely RD (2006) J Biol Chem 281:2012 35. Paczkowski FA, Sharpe IA, Dutertre S, Lewis RJ (2007) J Biol Chem 282:17837 36. Zhou Z, Zhen J, Karpowich NK, Goetz RM, Law CJ, Reith MEA, Wang D-N (2007) Science 317:1390 37. Butler SG, Meegan MJ (2008) Curr Med Chem 15:1737 38. Chen Z, Skolnick P (2007) Expert Opin Investig Drugs 16:1365 39. Frampton JE, Plosker GL (2007) CNS Drugs 21:581 40. Smith T, Nicholson RA (2007) Vasc Health Risk Manag 3:833 41. Üc¸eleyer N, Offenbächer M, Petzke F, Häuser W, Sommer C (2008) Neuropsych Dis Treat 4:525 42. Agur W, Abrams P (2007) Expert Rev Obstet Gynecol 2:133 43. Hartford JA, Kornstein SB, Liebowitz MC, Pigott TD, Russell JE, Detke MEFG, Walker DE, Ball SEF, Dunayevich EE, Dinkel JE, Erickson JE (2007) Int Clin Psychopharmacol 22:167 44. Ritz MC, Lamb RJ, Goldberg SR, Kuhar MJ (1987) Science 237:1219 45. Rocha BA, Fumagalli F, Gainetdinov RR, Jones SR, Ator R, Giros B, Miller GW, Caron MG (1998) Nat Neurosci 1:132 46. Sora I, Wichems C, Takahashi N, Li XF, Zeng Z, Revay R, Lesch KP, Murphy DL, Uhl GR (1998) Proc Natl Acad Sci USA 95:7699

Overview: Transporters as Targets for Drug Discovery 13 47. Guastella J, Brecha N, Weigmann C, Lester HA, Davidson N (1992) Proc Natl Acad Sci USA 89:7189 48. Liu QR, López-Corcuera B, Mandiyan S, Nelson H, Nelson N (1993) J Biol Chem 268:22802 49. Smith KE, Borden LA, Hartig PR, Branchek T, Weinshank RL (1992) Neuron 8:927

Top Med Chem (2009) 4: 15–51 DOI 10.1007/7355_2008_023  Springer-Verlag Berlin Heidelberg Published online: 22 May 2008 Membrane Transporters: Structure, Function and Targets for Drug Design Aina W. Ravna · Georg Sager · Svein G. Dahl · Ingebrigt Sylte (✉) Department of Pharmacology, Institute of Medical Biology, Faculty of Medicine, University of Tromsø, 9037 Tromsø, Norway [email protected] 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 2 Membrane Protein Structures . . . . . . . . . . . . . . . . . . . . . . . . . 19 3 Membrane Transporter Proteins . . . . . . . . . . . . . . . . . . . . . . . . 20 3.1 Classification of Membrane Transport Proteins . . . . . . . . . . . . . . . . 21 3.1.1 Facilitated Diffusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 3.1.2 Active Transport Mechanisms . . . . . . . . . . . . . . . . . . . . . . . . . 22 4 Structure Determination of Membrane Proteins . . . . . . . . . . . . . . . 24 4.1 Expression and Purification of Membrane Proteins . . . . . . . . . . . . . . 25 4.2 Structure Determination of Membrane Proteins . . . . . . . . . . . . . . . 26 4.2.1 X-Ray Crystallography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 4.2.2 NMR Spectroscopy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 4.2.3 Electron Microscopy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 4.2.4 Three-Dimensional Structure Prediction . . . . . . . . . . . . . . . . . . . 28 5 Transporters of Known 3D Structure . . . . . . . . . . . . . . . . . . . . . 29 5.1 The Major Facilitator Superfamily . . . . . . . . . . . . . . . . . . . . . . . 29 5.2 The Resistance-Nodulation-Cell Division Superfamily . . . . . . . . . . . . 31 5.3 The Drug/Metabolite Transporter Superfamily . . . . . . . . . . . . . . . . 32 5.4 The Neurotransmitter:Sodium Symporter Family . . . . . . . . . . . . . . . 32 5.5 The Dicarboxylate/Amino Acid:Cation (Na+ or H+ ) Symporter Family . . . 34 5.6 The ATP-Binding Cassette Superfamily . . . . . . . . . . . . . . . . . . . . 35 6 Potential for New Drug Development . . . . . . . . . . . . . . . . . . . . . 36 6.1 Multidrug Resistance Protein Targets . . . . . . . . . . . . . . . . . . . . . 36 6.1.1 ABC Transporters and Cancer Therapy . . . . . . . . . . . . . . . . . . . . 37 6.2 Multidrug Resistance and Antibiotic Treatment . . . . . . . . . . . . . . . . 39 6.3 CNS Drug Targets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 6.3.1 Neurotransmitter:Sodium Symporter Family . . . . . . . . . . . . . . . . . 39 6.3.2 The Drug:H+ Antiporter-1 (DHA1) (12 Spanner) Family . . . . . . . . . . 43 6.3.3 The Dicarboxylate/Amino Acid:Cation (Na+ or H+ ) Symporter Family . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 6.4 Transporters Involved in Drug Absorption, Distribution and Elimination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 6.5 Prodrug Targets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 6.5.1 Dipeptide Transporters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

16 A.W. Ravna et al. 7 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 Abstract Current therapeutic drugs act on four main types of molecular targets: enzymes, receptors, ion channels and transporters, among which a major part (60–70%) are membrane proteins. This review discusses the molecular structures and potential impact of membrane transporter proteins on new drug discovery. The three-dimensional (3D) molecular structure of a protein contains information about the active site and possible ligand binding, and about evolutionary relationships within the protein family. Transporters have a recognition site for a particular substrate, which may be used as a target for drugs inhibiting the transporter or acting as a false substrate. Three groups of transporters have particular interest as drug targets: the major facilitator superfamily, which includes almost 4000 different proteins transporting sugars, polyols, drugs, neurotransmitters, metabolites, amino acids, peptides, organic and inorganic anions and many other substrates; the ATP-binding cassette superfamily, which plays an important role in multidrug resistance in cancer chemotherapy; and the neurotransmitter:sodium symporter family, which includes the molecular targets for some of the most widely used psychotropic drugs. Recent technical advances have increased the number of known 3D structures of membrane transporters, and demonstrated that they form a divergent group of proteins with large conformational flexibility which facilitates transport of the substrate. Keywords Three-dimensional structure · Drug discovery · Drug targets · Membrane proteins · Transporters Abbreviations ABC ATP-binding cassette ATP Adenosine triphosphate cGMP Cyclic guanosine monophosphate CNS Central nervous system 2D Two dimensional 3D Three dimensional DAACS Dicarboxylate/amino acid:cation symporter DAT Dopamine transporter DHA1 Drug:H+ antiporter-1 DMT Drug/metabolite transporter DNA Deoxyribonucleic acid EAAT Excitatory amino acid transporter E-MeP European Membrane Protein Consortium EU European Union GABA Gamma-aminobutyric acid GAT GABA transporter GLUT Glucose transporter HAE Hydrophobe/amphiphile efflux HIV Human immunodeficiency virus 5-HT 5-Hydroxytryptamine (serotonin) MFS Major facilitator superfamily MS Mass spectrometry

Membrane Transporters: Structure, Function and Targets for Drug Design 17 NARI Noradrenaline reuptake inhibitor NBD Nucleotide binding domain NET Noradrenaline transporter NMR Nuclear magnetic resonance NSS Neurotransmitter:sodium symporter OAT Organic anion transporter PDB Protein data bank PEPT Dipeptide transporter PEPT1 H+ /dipeptide symporter PfHT Parasite-encoded facilitative hexose transporter RMSD Root mean square difference RNA Ribonucleic acid RND Resistance-nodulation-cell division SERT Serotonin transporter SMR Small multidrug resistance SSRI Selective serotonin reuptake inhibitor TC Transporter classification TCDB Transport classification database TMD Trans-membrane domain TMH Trans-membrane helix VMAT Vesicular monoamine transporter 1 Introduction A number of consortia bringing together researchers from academic research institutions and companies have been established to determine the three-dimensional (3D) structures of proteins, rapidly and cost-effectively using modern methodologies [1]. At the end of April 2007, the number of entities in the PDB database (http://www.rcsb.org/pdb/) was greater than 42 000. The number of entities in the PDB database increased by more than 5000 during 2006, which is equivalent to the total number of entities in the database 10 years ago. Genome sequencing together with significant advances in process automation and informatics have aided the development of highthroughput X-ray crystallography, and are the main reasons for the large increase in the number of available 3D structures. Atomic-resolution 3D structures provide important knowledge on biologically active molecules. The molecular structure of a protein contains information about the active site architecture, possible ligand or antigen binding sites, and evolutionary relationships within the protein family, and may serve as a basis for designing protein engineering experiments. The shape and electrostatic properties obtained from the molecular structure are also important for predicting possible interaction partners involved in regulation and complexation. Knowledge of the 3D structures of drug-target complexes defines the topography of the complementary surface between the drug target

18 A.W. Ravna et al. and the ligands, and provides the possibility of virtual screening experiments searching for possible new molecules binding to the target [2] and for structure-aided drug design [3]. When detailed structural data for the target protein are available, computer programs can be used for ligand docking and virtual screening of compound libraries, and to predict protein–ligand binding affinities in the search for possible lead compounds. The obtained information can help the synthetic chemist to optimize compounds by including chemical groups that can form better interactions with the target, resulting in improved potency and selectivity [4]. At the moment there are several drugs on the market originating from a structure-based design approach. Examples include the HIV drugs Agenerase and Viracept developed using the X-ray crystal structure of HIV proteinase [5, 6], development of the flu drug Zanamivir based on the X-ray structure of neuraminidase [7], and the angiotensin-converting enzyme inhibitors [8, 9]. Direct structural determination by experimental methods like NMR spectroscopy and X-ray crystallography, and indirect structural knowledge obtained by different biophysical and molecular biology studies, together with bioinformatics and computational chemistry are of pivotal importance in the discovery and development of biologically active molecules, and of more effective and safer drugs. During the last few years progress in genome sequencing has provided, and still provides, important information about the genetic map of different organisms. Modern technologies, such as microarray technology and 2D electrophoresis/mass spectrometry (MS), have provided insight into regulatory mechanisms at the DNA, RNA and protein levels. In the post-genomic era, focus will be on understanding the cellular machinery for regulation and communication, and how proteins and other gene products cooperate on a detailed atomic level. Such information provides insight into biological mechanisms and disease processes, and is important for the discovery and development of new drugs. However, knowledge of the detailed 3D structure of molecules involved in cellular communication will also be important in order to understand the cellular machinery. Structural information about central macromolecules and their regulation and interaction partners will most probably contribute to the discovery of new targets for therapeutic intervention, and may also give new insight into how drug targets can be therapeutically exploited. The drugs of the future may not only be traditional ligands functioning as an agonist, antagonist, substrate or inhibitor, but also act as scaffolding ligands by promoting protein–protein association, by preventing protein–protein association, or by enhancing or preventing degradation, internalization, etc. Future drugs may even be able to interfere with the specific signalling pathway(s) of a receptor without interfering with the other pathway(s) of the same receptor. Structural biology techniques, including theoretical calculations, and 3D structural information may therefore become even more important in the future.

Membrane Transporters: Structure, Function and Targets for Drug Design 19 Membrane transporter proteins are crucial co-players in cellular processes, and are known molecular components of many disease processes. The membrane transporter proteins are targeted by several presently used drugs, and have a large potential as targets for new drug development. In this review we discuss the current structural knowledge of membrane transporter proteins and its impact on new drug discovery. 2 Membrane Protein Structures The protein targets for drug action on mammalian cells can broadly be divided into four main types: receptors, enzymes, ion channels and transporters. Integral membrane proteins are involved in a variety of processes governing cellular functions, and provide a plethora of molecular targets for pharmacological intervention. A large number (60–70%) of the presently known drug targets are proteins embedded in a cellular membrane, and membrane proteins are among the most interesting macromolecules to study by structural biology techniques. High-resolution structural information about proteins embedded in a cellular membrane is of pivotal importance for developing new drugs with therapeutic potential, but is also important for the understanding of the molecular mechanisms of cellular communication and function. During the last few years, several international structural genomics networks have been established focusing on whole genomes [10], and some networks are focusing uniquely on membrane proteins. One of these networks is the EU-funded E-MeP consortium (http://www.ebi.ac.uk/e-mep/) that was established in 2005 with the goal of developing novel technologies to facilitate the purification and crystallization of membrane proteins. Currently around 20 European laboratories are members of the consortium, while additional laboratories are associate members. E-MeP is exploring several expression systems for 100 different prokaryotic and 200 different eukaryotic membrane proteins. Crystallization and structure determination of membrane proteins are still not straightforward processes, and current knowledge of the detailed 3D structures of membrane proteins is limited. Out of the more than 42 000 entities deposited in the PDB database, only around 0.3% are unique structures of membrane proteins, although membrane proteins are estimated to represent approximately one third of the proteins coded for in the human and other genomes [11, 12]. Some of the most important questions in the fields of biology, chemistry and medicine remain unsolved as a result of the currently limited understanding of the structure, behaviour and molecular interactions of membrane proteins. Integral membrane proteins of known 3D structure basically have two different types of architecture: α-helical bundles or β-barrels. Up to now,

20 A.W. Ravna et al. eukaryotic plasma and reticulum membrane proteins have been shown to be α-helical, while the β-barrel membrane proteins are mainly found in the outer membrane of Gram-negative bacteria and in mitochondria and chloroplast membranes [13]. The helix bundle proteins contain quite long transmembrane hydrophobic α-helices that are packed together into bundles with relatively complicated structure, while the β-barrel proteins are large proteins consisting of anti-parallel β-sheets that fold into a barrel closed by the first and last strands of the sheet [14, 15]. In amino acid sequences of proteins with unknown 3D structure and function, the long hydrophobic transmembrane α-helices are easier to recognize in the sequence than the less hydrophobic trans-membrane β-strands. Bioinformatics studies are therefore generally easier to perform for α-helical bundle trans-membrane proteins than for β-barrel trans-membrane proteins, and have produced much more information about α-helical bundle proteins. Since the 3D structure of integral membrane proteins is not easily determined experimentally, prediction of the secondary structure from the amino acid sequence is important for annotating protein sequences to membrane protein families. This, together with recognition of structural motifs by bioinformatics, provides structural information of value for determining the function and predicting the 3D structure of trans-membrane proteins [16–18]. 3 Membrane Transporter Proteins Ions and small organic molecules are often too polar to penetrate the cellular membrane on their own, and require a transport protein. Trans-membrane solute transporters may be divided into channels that function as selective pores opening in response to a chemical or electrophysiological stimulus, thus allowing movement of a solute down an electrochemical gradient, and active carrier proteins which use an energy-producing process to translocate a substrate against a concentration gradient [19]. Transporter proteins have a recognition site making them specific for a particular solute. The human genome contains many different transporters, including those responsible for the transport of glucose and amino acids into cells, transport of ions and organic molecules by the renal tubules, transport of Ca2+ and Na+ out of cells, uptake of neurotransmitters and neurotransmitter precursors into nerve terminals and vesicles, and transporters involved in multidrug resistance. Drugs may exert their effect by binding to transporters and either inhibiting transport of the solute or functioning as a false substrate for the transport process. Examples of such drugs include the antidepressant drugs that inhibit the neuronal transporters for noradrenaline and serotonin [20, 21], probenecid which inhibits the weak acid transporter protein in the renal tubule [22], loop

Membrane Transporters: Structure, Function and Targets for Drug Design 21 diuretics inhibiting the Na+ /K+ /2Cl– co-transporter of the loop of Henle [23], and the irreversible inhibitor of the H+ /K+ ATPase (proton pump) of the gastric mucosa, omeprazole [24]. The lack of atomic-resolution 3D structures of membrane transporter proteins limits the design of new ligands interfering with the structure and function of the transporter. Only a few membrane transporter proteins from bacterial species have been crystallized and examined by X-ray diffraction experiments [25]. This makes molecular modelling by biocomputing an interesting methodological alternative, and in many cases the only method available for structural studies of membrane transporter proteins. However, such methods depend on a combination of computational techniques and experimental structural information to guide the molecular modelling process. 3.1 Classification of Membrane Transport Proteins According to the classification approved by the transporter nomenclature panel of the International Union of Biochemistry and Molecular Biology [19], transporters belong to six categories: 1. Channels and pores 2. Electrochemical potential-driven transporters (secondary and tertiary transporters) 3. Primary active transporters 4. Group translocators 8. Accessory factors involved in transport 9. Incompletely characterized transport proteins Categories 2, 3 and 4 are carriers. In contrast to most channels, carriers exhibit stereospecific substrate specificities, and their rates of transport are several orders of magnitude lower than those of other channels [19]. Mammalian species have carriers for peptides, nucleosides, sugars, bile acids, amino acids, organic anions, organic cations, vitamins, fatty acids, bicarbonate, phosphates and neurotransmitters. Numerous transporters of interest as drug targets belong to subclasses 2A (porters) and 3A (diphosphate bond hydrolysis-driven transporters). Porters are either uniporters, symporters or antiporters. Uniporters are facilitated diffusion carriers that transport single molecules, symporters transport two or more molecules in the same direction, while antiporters transport two or more molecules in opposite directions [19]. Carrier mechanisms are distinguished by the source of energy used to activate the transporter, which may be either one of two: • Facilitated diffusion • Active transport

22 A.W. Ravna et al. 3.1.1 Facilitated Diffusion Facilitated diffusion is accelerated by specific binding between the solute and the transporter. The solute flows from a higher to a lower electrochemical potential, so-called passive transport, via a uniporter, and facilitated diffusion therefore does not require a supply of energy. Examples of uniporters, or facilitated diffusion transporters, are glucose transporters (GLUTs), as indicated in Fig. 1, and the parasite-encoded facilitative hexose transporter (PfHT) of the major facilitator superfamily (MFS). Examples of GLUTs are GLUT1 and GLUT2. GLUT1 is expressed in highest concentrations in erythrocytes and in endothelial cells of barrier tissues, such as the blood–brain barrier. GLUT2 is expressed in liver cells, pancreatic beta-cells, renal tubular cells and intestinal epithelial cells that transport glucose. GLUT1 is responsible for the basal glucose uptake required to maintain respiration in all cells, and GLUT1 levels are decreased by increased glucose levels and increased by decreased glucose levels. PfHT is used by the malaria parasite to absorb glucose, which it needs to grow and multiply in red blood cells. Fig. 1 Facilitated diffusion of glucose through GLUT down the concentration gradient 3.1.2 Active Transport Mechanisms Active transport uses the free energy stored in the high-energy phosphate bonds of adenosine triphosphate (ATP) as energy source to activate the transporter. There are three types of active transport mechanisms: primary active transport, secondary active transport and tertiary active transport. Primary active transporters (Fig. 2) use the energy from ATP directly. They exhibit ATPase activity to cleave ATP’s terminal phosphate, and move substances from regions of low concentration to regions of high concentration. The ATP-binding cassette (ABC) transporters are primary active transporters comprising a family of structurally related membrane proteins that share a common intracellular structural motif in the domain that binds and hydrolyses ATP. ABC transporters are molecular pumps that regulate the movement of diverse molecules across cellular membranes and represent an

Membrane Transporters: Structure, Function and Targets for Drug Design 23 Fig. 2 Primary active transport of drug via P-glycoprotein. The energy from ATP is used to expel the drug out of the cell important class of targets for discovery of novel small-molecule drugs for treatment of a broad range of human diseases. ABC transporters have both trans-membrane domains (TMDs) and nucleotide binding domains (NBDs). The domain arrangement of these transporters is generally TMD-NBDTMD-NBD, but domain arrangements such as TMD-TMD-NBD-TMD-NBD, NBD-TMD-NBD-TMD, TMD-NBD and NBD-TMD have also been demonstrated [26, 27]. ABC transporters can be either exporters or importers. A well-characterized ABC exporter is P-glycoprotein, or ABCB1, which is widely distributed in normal cells, such as liver cells, renal proximal tubular cells, cells lining the intestine and the capillary endothelial cells of the blood– brain barrier. P-glycoprotein has broad substrate specificity and may have evolved as a defence mechanism against toxic substances. It actively pumps chemotherapeutic agents out of cancer cells, resulting in multidrug resistance to such drugs (Fig. 2). Secondary active transporters (Fig. 3) use the energy from a concentration gradient previously established by a primary active transport process. Thus, secondary active transport indirectly uses the energy derived from the hydrolysis of ATP. The driving force of secondary active transport is an ion, for instance H+ or Na+, transported down its concentration gradient. Simultaneously, a substrate is transported against its concentration gradient. There are two types of secondary active transport processes: antiport and symport. In antiport, the driving force ion and the substrate are transported Fig. 3 Secondary active transport. The energy established by the Na + gradient is used to transport serotonin against its concentration gradient

24 A.W. Ravna et al. in opposite directions, while in symport, they are transported in the same direction. Examples of secondary transporters are the H+ /dipeptide symporter (PEPT1) mainly involved in absorption of di- and tripeptides across plasma membranes in the small intestine and kidney proximal tubules, and central nervous system (CNS) transporters such as the serotonin (5-HT) transporter (SERT), noradrenaline transporter (NET), dopamine transporter (DAT), GABA transporter (GAT) and excitatory amino acid (glutamate) transporter (EAAT). By pumping neurotransmitters back into presynaptic nerve terminals, these CNS transporters play central roles in maintaining the homeostasis of neutrotransmitter levels in neuronal synapses. Tertiary active transporters like the organic anion transporters (OATs). Tertiary active transporters utilize a gradient generated by secondary active transport. OATs use the outwardly directed dicarboxylate gradient to move (exchange) the organic substrate into the cell. The dicarboxylate gradient is generated by the sodium dicarboxylate co-transporter (secondary active transporter) which is using the inwardly directed sodium gradient initially generated by the Na+ /K+ -ATPase (primary active transporter) [28]. 4 Structure Determination of Membrane Proteins Although structural determination of membrane proteins is not a trivial task, improvements in membrane protein molecular biology and biochemistry, technical advances in structural data collection, notably using synchrotron X-ray beamlines, and the availability of several sequenced genomes have contributed to progress in the number of trans-membrane proteins determined by X-ray crystallography [29–31]. The difficulties in experimental structure determination of trans-membrane proteins arise from their amphiphilic nature. The hydrophilic surfaces are exposed to the aqueous medium, while the hydrophobic surfaces interact with non-polar alkyl chains of phospholipids. The amphiphilic nature makes it difficult to obtain stable and homogeneous protein preparations, and during crystallization, crystal contacts are formed between hydrophilic and hydrophobic surfaces. Key issues that need to be considered before the structure of a transmembrane drug target can be determined are [10]: • How to produce a sufficient amount of the membrane protein. • How to solubilize and purify the membrane protein without destroying the active 3D conformation of the protein. For membrane transporter proteins this is not trivial, due to the hydrophobic nature of the membranespanning region of the protein. • How to crystallize the membrane transport protein, and what can be done in order to study the 3D membrane protein structure in solution.

Membrane Transporters: Structure, Function and Targets for Drug Design 25 4.1 Expression and Purification of Membrane Proteins In order to determine a protein structure at high resolution, at least milligram quantities of the protein are required. In spite of recombinant protein production techniques and a variety of available expression systems, it has been difficult to provide membrane proteins in a quantity and quality for X-ray crystallographic structure determination. Membrane proteins are often expressed in low abundance in native tissues, and it is therefore necessary to produce the proteins in heterologous expression systems. However, heterologous membrane protein expression may produce toxic effects on host cells, contributing to poor stability and low yields [1]. This problem can be reduced by introducing deletions and mutations into the proteins and by generating fusion constructs. It is also important to use an expression system that does not significantly affect the activity of the mammalian membrane protein, compared with the activity in the native tissue [10]. Prokaryotes may lack many post-translational modification systems of importance for the native activity of the membrane protein. Many different types of recombinant expression systems have been tested for membrane proteins. The most widely used system for recombinant protein expression of transmembrane proteins has been Escherichia coli, due to the simple and inexpensive scale-up [32], which has so far also been the most successful approach. The expression has been directed to the bacterial membrane or inclusion bodies. Suitable expression vectors are available, and proteins can be labelled metabolically with heavy-atom-labelled amino acids for X-ray crystallography or with stable isotopes for NMR spectroscopy [33]. In addition to E. coli, other bacteria have also been tested for membrane protein expression, but have usually given lower yields [34]. Different yeast strains have been used for recombinant expression of a number of trans-membrane proteins [10]. Insect cells have a close resemblance to mammalian cells and have been used for membrane protein expression [10, 35]. Expression in mammalian cells has also been performed, resulting in both transient and stable expression. A general drawback with the use of mammalian cell lines has been that it has given quite low yields compared with bacterial expression systems, and it also involves a more timeconsuming procedure [36]. Expression in COS cells and HEK293 cells has successfully been done for membrane transporter proteins including the glutamate transporter [37, 38]. After expression, the protein is solubilized and separated from the lipid components by the use of detergents. This process very often requires an intensive screening process, since different detergents have to be used for different trans-membrane proteins [10]. After solubilization, the recombinant protein is often purified by affinity chromography methods, after insertion of histidine tags into the N- or C-terminal of the protein.

26 A.W. Ravna et al. 4.2 Structure Determination of Membrane Proteins The methods used to determine high-resolution atomic structures of proteins are nuclear magnetic resonance (NMR) spectroscopy and X-ray crystallography. Structural determination by X-ray crystallography is so far the method with largest success for trans-membrane proteins. X-ray crystallography and NMR have complementary features in elucidating the structure–functional relationships of proteins and protein–ligand complexes. If a protein forms suitable crystals, X-ray crystallography may represent a convenient and rapid approach, while NMR spectroscopy may have advantages when the structure is partly distorted, exists in several stable conformations in solution or does not crystallize. Solution and solid-phase NMR are also alternatives for structure determination, especially for smaller proteins, but also for protein domains where the electron density is not observed by X-ray crystallography. This is exemplified by the solution NMR structure of the periplasmic signalling domains of the TonB-dependent outer membrane transporter FecA from E. coli [39]. Electron cryomicroscopy also contributes valuable structural information about membrane proteins, although at much lower resolution than that obtained by X-ray crystallography [40]. Since structure determination of membrane proteins by experimental methods has so far proven very challenging, structure prediction by homology modelling [25] using modern bioinformatics techniques may represent an alternative, and very often the only alternative, to obtain insight into the atomic structure of membrane transporters and other membrane proteins. 4.2.1 X-Ray Crystallography The use of advanced protein expression and purification procedures, crystallization robots and powerful synchrotron radiation sources has enabled high-throughput structure determination using X-ray crystallographic techniques. Crystallization techniques and structure determination have become “high-throughput” for several protein families, but for membrane proteins including transporter proteins, the available crystallization and structure solution methods are not regarded as high throughput. A high-resolution X-ray crystallographic structure provides structural information at an atomic level and is a powerful method for studying the structure of drug targets and their ligands. X-ray crystal structures represent time and space averages of all atoms present within the protein molecule, and may also provide information about the structural movements of the protein. The process of X-ray structure determination of trans-membrane proteins has different steps including crystallization of the purified membrane pro-

Membrane Transporters: Structure, Function and Targets for Drug Design 27 tein, measurements of crystal diffractions, calculation of electron density and model building [1, 10]. A major challenge of X-ray crystallography of trans-membrane proteins is to obtain suitable 3D crystals. Homogeneity and stability at high protein concentrations are important to obtain good results. Different strategies have been used for producing suitable crystals. These strategies include the use of detergents that replace the native membrane lipids and form mixed detergent–membrane protein micelles, crystallization using vapour diffusion, and crystallization using lipid cubic phases and bicelles [29]. The rationale behind the methods using cubic phases [41–43] or bicelles [44, 45] is that the solubilized membrane protein is inserted into a native-like environment that is believed to improve the chances of crystallization. 4.2.2 NMR Spectroscopy NMR spectroscopy investigates transition between spin states of magnetically active nuclei in a magnetic field. Determination of the solution structure of trans-membrane proteins by NMR requires that well-resolved 2D 1H/15N chemical shift correlation spectra can be obtained. For helical transmembrane proteins, spectral resolution is complicated by the limited amide 1H chemical shift dispersion in α-helixes and the slow correlation time for many micelle-bound proteins [46]. In general, NMR methods have advanced to the point where small to medium sized protein domain structures can be determined in a quite routine manner, and solution NMR spectroscopy has emerged as an eminent tool in studies of protein structure [47] and intermolecular interactions [48]. Of about 42 000 entities (April 2007) deposited in the PDB database (http://www.rcsb.org/pdb/), about 15% were determined by NMR techniques. NMR spectroscopy of proteins contributes with important information about the kinetics, thermodynamics, conformational equilibria, molecular motions and ligand binding equilibria of the protein, since the signals observed in solution by NMR show the chemical properties of atomic nuclei, including the their relative motions [49]. If over-expressed proteins are inserted efficiently into membranes, they might also be studied by solid-state NMR spectroscopy without prior dissociation. When this method can handle larger proteins, the method holds promise for 3D structure determination of membrane proteins [50, 51]. 4.2.3 Electron Microscopy The basic idea of electron microscopic 3D structure determination is to produce 2D projection images (2D crystals) from a 3D object. These 2D projec-

28 A.W. Ravna et al. tion images can then be used to reconstruct the 3D structure of the original object by applying back-projection algorithms [1]. The method can be used to study large macromolecular machines like the ribosome or spliceosome which undergo massive structural rearrangements [40]. A number of membrane proteins have been reconstituted to form 2D crystals. The quality of the diffraction in the best direction of optimum crystals typically ranges from about 6–7 ˚A resolution up to 3 ˚A. At around 6 ˚A resolution trans-membrane α-helices can be revealed [52], while at 3 ˚A the protein backbone and larger side chains can be modelled. 4.2.4 Three-Dimensional Structure Prediction Comparative modelling or homology modelling can be used to generate 3D structural models of proteins with unknown structure [53]. In homology modelling or comparative modelling, molecular modelling techniques are used to construct 3D models of the protein of interest (the target protein) using structural information from a protein with known 3D structure (the template protein), based on a postulated structural conservation between the template and target proteins. The homology modelling approach is based on the observation that the 3D structure of homologous proteins is more conserved than the amino acid sequence. Combined with structural information from molecular biology studies (e.g. site-directed mutagenesis experiments) and ligand binding studies, homology modelling provides indirect structural knowledge about the target protein and its interactions with drugs and other interaction partners. When the structural similarities between the target and the template protein are high, the homology modelling approach may give structural models of sufficient accuracy for virtual screening of compound libraries and targetbased ligand design. The accuracy of a model constructed by homology modelling depends on the conservation of secondary structure between the template and the target [54]. Sequence similarities larger than 50% between the template and the target are assumed to produce quite accurate structural models. Sequence similarities of 50% are expected to give a root mean square difference (RMSD) of about 1 ˚A between the backbone atoms of the template structure and the model. However, even at an overall sequence identity of <20% between the template and the target, the active sites and the secondary structure elements necessary for building the protein scaffold may have very similar geometries [55]. Several automatic homology modelling methods are available on the internet [56–58]. Such automatic modelling methods may provide models of high accuracy when the structural conservation between the template and the target is high. The most important single determinant for the quality of the homology-based model is the accuracy of the amino acid sequence

Membrane Transporters: Structure, Function and Targets for Drug Design 29 alignment between the template and the target [54]. For membrane transporters, the sequence identity between a bacterial template and a modelled mammalian membrane transporter is often low, and the alignment often has to be manually adjusted based on experimental observations, particularly from site-directed mutagenesis experiments [59]. The interpretation of site-directed mutagenesis results is therefore very important in the process of modelling membrane proteins. Models with low sequence similarity to the template structure are valuable working tools for generating hypotheses about the structure and function of the target protein, for designing new experimental studies, and along with structural information would contribute value to ligand design. 5 Transporters of Known 3D Structure Three-dimensional crystal structures of several bacterial transporters for organic molecules have been determined by X-ray crystallography at atomic resolution, as shown in Table 1. 5.1 The Major Facilitator Superfamily The major facilitator superfamily (MFS) includes almost 4000 different transporter proteins. The MFS family members transport diverse substrates including sugars, polyols, drugs, neurotransmitters, Krebs cycle metabolites, phosphorylated glycolytic intermediates, amino acids, peptides, organic and inorganic anions and many more (http://www.tcdb.org/) [60–63]. These transporters function by uniport, symport or antiport mechanisms, and may possess either 12 [64], 14 [65] or 24 [66] trans-membrane helices (TMHs), with a common evolutionary ancestor [67]. Examples of human MFS transporters are glucose uniporters (GLUTs), the vesicular monoamine transporter 1 and 2 (VMAT1 and VMAT2), the thyroid hormone transporter (MCT8) and the organic anion transporter (OAT) family. The 3D structures of three E. coli transporter proteins of the MFS family have been determined by X-ray crystallography at atomic resolution: EmrD [68] (Fig. 4a), GlpT [69] and LacY [70] (Fig. 4b), at 3.5, 3.3 and 3.5 ˚A, respectively. These structures indicate that MFS proteins with 12 TMHs share a common architecture of the membrane spanning region, organized in symmetrical N- and C-terminal domains each of six TMHs, with overall structural topologies resembling each other. TMHs 3, 6, 9 and 12 are facing away from the interior of the transporters [68–70] (Fig. 4). The orientations of the TMHs of EmrD are different from those of GlpT and LacY, presumably

30 A.W. Ravna et al. Table 1 Transporters for organic substrates with 3D structure determined at atomic resolution by X-ray crystallography. TC: transporter classification number (http://www.tcdb.org/) Name Family/superfamily Function Organism TC number PDB ident. Refs. EmrD (hydrophobic uncoupler, e.g. CCCP, benzalkonium, SDS):H+ antiporter Major facilitator superfamily (MFS) H+ antiport (multiple drugs) Escherichia coli 2.A.1.2.9 2gfp [68] GlpT (glycerol-P:Pi antiporter) Major facilitator superfamily (MFS) Pi/glycerol- 3-phosphate antiport Escherichia coli 2.A.1.4.3 1PW4 [69] LacY (lactose:H+ symporter) Major facilitator superfamily (MFS) Symport (lactose/H+) Escherichia coli 2.A.1.5.1 1PV6 1PV7 [70] AcrB (multidrug/dye/ detergent resistance pump) Resistance-nodulation-cell division (RND) superfamily H+ antiport Escherichia coli 2.A.6.2.2 1OY6 etc [73] EmrE (small multidrug efflux pump) Drug/metabolite transporter (DMT) superfamily H+ antiport Escherichia coli 2.A.7.1.3 1S7B 2F2M [82] LeuTAa (amino acid (leucine):2 Na+ symporter) Neurotransmitter:sodium symporter (NSS) family Na+ symport Aquifex aeolicus 2.A.22.4.2 2A65 [64] Gltph (archaeal glutamate transporter homologue) Dicarboxylate/amino acid:cation (Na+ or H+) symporter (DAACS) family H+ symport Pyrococcus horikoshii 2.A.23.1.5 11XFH [86] Sav1866 (multidrug exporter) ABC superfamily Staphylococcus aureus 3.A.1.106.2 2HYD [88] BtuCD (bacterial ABC transporter involved in B12 uptake) Vitamin B12 uptake transporter (B12T) family (ABC superfamily) Vitamin B12 uptake (ATP) Escherichia coli 3.A.1.13.1 1L7V [93] HI1470/1 (bacterial ABC transporter involved in haem and B12 uptake) Vitamin B12 uptake transporter (B12T) family (ABC superfamily) Haem and B12 uptake Haemophilus influenzae – 2NQ2 [94]

Membrane Transporters: Structure, Function and Targets for Drug Design 31 Fig. 4 Backbone Cα trace of the X-ray crystallographic structure of EmrD (a) [68] (PDB code 2GFP) and LacY (b) [70] (PDB code 1PV6), viewed in the membrane plane (cytoplasm downwards). Colour coding of the structures: blue via white to red from N-terminal to C-terminal because GlpT and LacY are facing the cytoplasm in a V-shaped conformation [69, 70], while EmrD probably represents an intermediate state [68]. It has been proposed that the substrates for GlpT, LacY and EmrD are translocated across the membrane by an alternating-access mechanism [68–70]. 5.2 The Resistance-Nodulation-Cell Division Superfamily All known members of the resistance-nodulation-cell division (RND) superfamily catalyse substrate efflux via and H+ antiporter mechanisms. These transporters are found in bacteria, archaea and eukaryotes and are organized in eight phylogenic families (http://www.tcdb.org/) [71, 72]. Up to now, 18 different X-ray crystallographic structures of the proton:drug antiporter Acriflavine resistance protein B (AcrB) have been reported [73–77] [78] (Fig. 5). This transporter is a major drug-resistance pump of the RND superfamily that belongs to the largely Gram-negative bacterial hydrophobe/amphiphile efflux-1 (HAE1) family (http://www.tcdb.org/). In E. coli the protein cooperates with a membrane fusion protein AcrA, and the outer membrane channel Tol C [73–75]. The substrate specificity of this large protein complex is broad, transporting cationic neutral and anionic substrates [79]. The AcrB protomer is organized as a homotrimer with a jellyfish-like structure [73], and the crystal structures of AcrB with and without substrates indicate that drugs are exported by a functionally rotating mechanism [74] or an alternating access peristaltic mechanism [75].

32 A.W. Ravna et al. Fig. 5 Backbone Cα trace of the X-ray crystallographic structure of a single AcrB protomer [73] (PDB code 1IWG) viewed in the membrane plane. Colour coding as in Fig. 4 5.3 The Drug/Metabolite Transporter Superfamily The drug/metabolite transporter (DMT) superfamily consists of 18 recognized families, each with a characteristic function, size and topology [80]. The multidrug transporter EmrE belongs to this superfamily, and to the four TMH small multidrug resistance (SMR) family (http://www.tcdb.org/). The SMR family members are prokaryotic transport systems consisting of homodimeric or heterodimeric structures [81]. Two E. coli EmrE X-ray crystal structures have been reported at 3.7 [82] and 3.8 ˚A [83]. The EmrE transporter is a proton drug:antiporter [82], and two EmrE subunits form a homodimer that binds substrate at the interface [83] (Fig. 6). 5.4 The Neurotransmitter:Sodium Symporter Family Members of the neurotransmitter:sodium symporter (NSS) family catalyse uptake of a variety of neurotransmitters, amino acids, osmolytes and related nitrogenous substances by a solute:Na+ symport mechanism [84]. In 2005 the crystal structure of the Aquifex aeolicus LeuTAa determined by X-ray diffrac-

Membrane Transporters: Structure, Function and Targets for Drug Design 33 Fig. 6 Cα trace of the X-ray crystal structure of the EmrE dimer X [83] (PDB code 2F2M) viewed in the membrane plane. Colour coding as in Fig. 4 Fig. 7 Cα trace of the LeuTAa X-ray crystallographic structure [64] (PDB code 2A65) viewed in the membrane plane. Colour coding as in Fig. 4 tion at 1.65 ˚A resolution was reported [64] (Fig. 7). LeuTAa belongs to the NSS family (http://www.tcdb.org/), and is a bacterial homologue of SERT, DAT, NET and GAT-1. It is a 12 TMH sodium/leucine symporter, where TMHs 1–

34 A.W. Ravna et al. 5 are related to TMHs 6–10 by a pseudo-twofold axis in the membrane plane. The structure resembles a shallow “shot glass” [64], with leucine and sodium ions bound within the protein core. The substrate and sodium ion binding sites are comprised of TMHs 1, 3, 6 and 8. An alternating access model for transport, where all symported substrates must bind simultaneously before translocation, has been confirmed by experimental studies on SERT [85]. 5.5 The Dicarboxylate/Amino Acid:Cation (Na+ or H+ ) Symporter Family The members of the dicarboxylate/amino acid:cation symporter (DAACS) family catalyse Na+ and/or H+ symport together with either a Krebs cycle dicarboxylate (malate, succinate or fumarate), a dicarboxylic amino acid (glutamate or aspartate), a small, semipolar, neutral amino acid (Ala, Ser, Cys, Thr), neutral and acidic amino acids or most zwitterionic and dibasic amino acids (http://www.tcdb.org/). The Pyrococcus horikoshii Gltph (archaeal glutamate transporter homologue) structure has been determined by X-ray crystallography at 3.5 ˚A resolution [86] (Fig. 8) and 2.96 ˚A resolution [87]. This is a proton symporter belonging to the DAACS family (http://www.tcdb.org/). The transporter is organized as a trimer, with each protomer having eight TMHs, two re-entrant helical hairpins, and independent substrate translocation pathways [87]. It has been proposed that glutamate transport is achieved by movements of the Fig. 8 Backbone Cα trace of the Gltph trimer [86] (PDB code 1XFH) viewed in the membrane plane. The three protein subunits are shown in different colours (red, green, blue)

Membrane Transporters: Structure, Function and Targets for Drug Design 35 hairpins allowing alternating access to either side of the membrane [86]. Gltph is a bacterial homologue of the human EAAT1–5. 5.6 The ATP-Binding Cassette Superfamily The ABC superfamily contains both uptake and efflux transport systems. Phylogenically, the members of these two porter groups generally cluster loosely together with just a few exceptions. There are dozens of families within the ABC superfamily, and family classification generally correlates with substrate specificity (http://www.tcdb.org/). In 2006, the multidrug transporter Staphylococcus aureus Sav1866 was determined by X-ray crystallography at 3.0 ˚A resolution in an outward-facing conformation, reflecting the ATP-bound state [88]. Sav1866 belongs to the ABC superfamily and shows sequence similarity to human P-glycoprotein (P-gp). The transporter consists of two subunits, each with a trans-membrane domain–nuclear binding domain (TMD-NBD) topology, with six TMHs in each TMD. The two subunits are twisted and embracing each other, and both the TMDs and NBDs are tightly interacting. Towards the extracellular side, bundles of TMHs diverge into two “wings”, with each wing consisting of TMH1 and TMH2 from one subunit and TMH3–TMH6 from the other subunit. The crystal structure of Sav1866 indicates that ABC transporters may use an “alternating access and release” mechanism where ATP binding and hydrolysis control the conversion of one state into the other, and that domain swapping and subunit twisting takes place in the transport cycle [88]. The MsbA structures from three different bacteria have been determined by X-ray crystallography at 4.5 ˚A resolution (E. coli) [89], 3.8 ˚A resolution (Vibrio cholerae) [90], and 4.2 ˚A resolution (Salmonella typhimurium) [91]. The MsbA transporters belong to the ABC superfamily, and the prokaryotic ABC-type efflux permeases or the lipid exporter (LipidE) family (http://www.tcdb.org/). The three different structures were thought to represent different conformational stages of the transport cycle, an open conformation [89], a closed conformation [90], and a post-hydrolysis conformation [91]. If true, the MsbA structures would represent interesting targets for computer modelling of human ABC transporters. However, these structures were retracted [92] after the publication of the Sav1866 structure [88]. The Sav1866 structure indicated that the MsbA structures were incorrect and that the biological interpretations based on the MsbA structures were invalid. The E. coli BtuCD protein is involved in B12 uptake, and the structure was determined by X-ray crystallography at 3.2 ˚A resolution [93]. BtuCD also belongs to the ABC superfamily, prokaryotic ABC-type uptake permeases, and the vitamin B12 uptake transporter (B12T) family. It consists of four subunits, two NBDs (BtuD) and two TMDs (BtuC). Each of the two BtuC subunits contains ten TMHs [93].

36 A.W. Ravna et al. Fig. 9 Backbone Cα trace of the Sav1866 dimer [88] (PDB code 2HYD) viewed in the membrane plane. The NBDs are in red, while the TMDs are coloured in blue to white from the N- to the C-terminal The 3D structure of the HI1470/1 transporter from Haemophilus influenzae, which is also a bacterial ABC transporter mediating the uptake of metal-chelate species including haem and vitamin B12, has been determined at 2.4 ˚A resolution [94]. It exhibits an inward-facing conformation, which is in contrast to the outward-facing state observed for the homologous vitamin B12 importer BtuCD [94]. The 3D structures indicate that the substrate translocation requires large conformational changes, and the differences between the BtuCD and the HI1470/1 transporter from H. influenzae may reflect conformations relevant to the alternating access mechanism of substrate translocation. 6 Potential for New Drug Development 6.1 Multidrug Resistance Protein Targets Cells exposed to toxic compounds can develop resistance by a number of mechanisms, including increased excretion. This may result in multidrug

Membrane Transporters: Structure, Function and Targets for Drug Design 37 resistance, which is a particular limitation to cancer chemotherapy and antibiotic treatment. Development of inhibitors of drug efflux transporters has been sought for use as a supplement to current therapy in order to overcome multidrug resistance problems [95]. 6.1.1 ABC Transporters and Cancer Therapy ABC transporters play an important role in multidrug resistance in cancer chemotherapy. Human ABC transporters are divided into five different subfamilies ABCA, ABCB, ABCC, ABCD and ABCG, based on phylogenetic analysis. According to the transport classification database (TCDB), these ABC transporter subfamilies (ABC-type efflux permeases) belong to subclasses 3.A.1.201–212 [19] (http://www.tcdb.org/). Transporters in subfamilies ABCA, ABCB, ABCC and ABCG are involved in multidrug resistance [96–99]. ABCB1 (P-Glycoprotein) The ABCB1 transporter is important in the removal of anticancer agents, such as adriamycin, vincristine and daunorubicin, from cells. ABCB1 is expressed in normal tissues, such as the gastrointestinal epithelium, epithelia of the bronchi, mammary gland, prostate gland, salivary gland, sweat glands of the skin, pancreatic ducts, renal tubules, and in bile canaliculi and ductules, in adrenal and in endothelial cells at blood–brain barrier sites and other blood– tissue barrier sites [100]. ABCB1 expression is highest in tumours from colon, adrenal, pancreatic, mammary and renal tissue, even in the absence of prior chemotherapy [101]. Even though the relationship between ABCB1 expression and response to chemotherapy remains unclear, negative prognostic implications of ABCB1 expression have been established in breast cancer, neuroblastoma, various types of leukaemia, and several sarcomas [101]. Development of ABCB1 inhibitors may help to prevent ABCB1 efflux of anticancer agents. ABCB1 inhibitors are not cytotoxic agents themselves, but when used in combination with cancer drugs which are normally pumped out by the cell by ABCB1, intracellular drug concentrations are maintained, restoring sensitivity to these therapeutics. Three generations of ABCB1 inhibitors have been developed. The firstgeneration ABCB1 inhibitors were established therapeutic drugs for diverse targets that were discovered, largely by chance, to also function as ABCB1 inhibitors [101]. In general, these were less potent than later generations of ABCB1 inhibitors; they were not selective, and produced undesirable side effects [95]. The second-generation ABCB1 inhibitors, which were based on the structures of the first-generation compounds and optimized using QSAR [101], were less toxic. However, inhibition of ABCB1 by first- or secondgeneration compounds has failed to demonstrate the desired clinical benefit.

38 A.W. Ravna et al. Dangerously high doses of these agents were needed, and they exhibited toxicity due to an increased availability of the co-administered chemotherapy [95]. The third-generation ABCB1 inhibitors, which were discovered by combinatorial chemistry screening [101], are more potent and more selective than earlier compounds, and are currently in clinical trials [101, 102]. The therapeutic benefit of ABCB1 inhibition is yet to be firmly established, but the continued development of these agents may establish the true therapeutic potential of ABCB1-mediated multidrug resistance reversal. A suggested approach would achieve a balance between the positive effects of ABCB1 inhibition at the tumour site and the negative potential toxic side effects outcome of reducing elimination of the chemotherapy. ABCC5 (MRP5) ABCC5 belongs to the ABC superfamily, transports cGMP and is also involved in multidrug resistance [103]. ABCC5 is expressed in most tissues, such as in skeletal muscle, kidney, testis, heart and brain [104–106], in smooth muscle cells of the corpus cavernosum, ureter and bladder, and mucosa in ureter and urethra [107, 108], in vascular smooth muscle cells, cardiomyocytes, and vascular endothelial cells in the heart [109], in placenta [110], and in human erythrocytes [103]. Clinical studies have shown that extracellular cGMP levels are elevated in various types of cancer. Significant elevation of urinary cGMP excretion has been observed in patients with untreatable adenocarcinomas from ovary, stomach or large bowel, whereas a normal range was found in patients where tumours had been removed [111]. Elevated urine cGMP concentrations have also been demonstrated among patients with cancer of the uterine cervix [112], and measurements of urinary cGMP levels after treatment of ovarian cancer has been reported to be a very sensitive tool in therapeutic monitoring [113–115]. Increased cGMP efflux by ABCC5 may be one mechanism whereby cancer cells can develop resistance against endogenous growth control, and also against antineoplastic drugs which are substrates for ABCC5. ABCB1/ABCC5 Structural Considerations/Molecular Modelling Approach Knowledge of the ABCB1 and ABCC5 structures may be used to develop membrane transport modulating agents which, in turn, may be helpful in overcoming resistance to chemotherapeutic agents. These transporters feature both TMDs and NBDs, with a TMD-NBD-TMD-NBD domain arrangement. The NBD contains the Walker A and B motifs [116] and a signature C motif, and the substrate specificity of the transporters is provided by the TMDs. The 3D structures of ABCB1 and ABCC5 have not been experimentally determined, but molecular modelling by homology may be used to gain

Membrane Transporters: Structure, Function and Targets for Drug Design 39 structural insight into their potential as drug targets. In particular, homology modelling may be used to study substrate difference between ABCB1 and ABCC5, since ABCB1 transports cationic amphiphilic and lipophilic substrates [117–120], while ABCC5 transports organic anions [103, 121]. In order to understand the molecular concepts underlying the substrate difference between ABCB1 and ABCC5, we have used the Staphylococcus aureus Sav1866 X-ray crystal structure [88] to construct models of ABCB1 and ABCC5 [122]. Modelling indicated that the electrostatic potential surface of the substrate translocation area of ABCB1 is neutral with negative and weakly positive areas, while the electrostatic potential surface of the ABCC5 substrate translocation chamber generally is positive. These results indicate that ABCB1, transporting cationic amphiphilic and lipophilic substrates, has a more neutral substrate translocation chamber than ABCC5, which has a positive chamber transporting organic anions. Structural information about the ABCB1 and ABCC5 substrate binding sites might be useful in the design of inhibitor multidrug efflux by these transporters. 6.2 Multidrug Resistance and Antibiotic Treatment Treatment of infections may be limited by the emergence of bacteria that are resistant to multiple antibiotics. Bacterial antibiotic resistance may be caused by intrinsic mechanisms, such as efflux systems, or by acquired mechanisms, such as mutations in genes targeted by the antibiotic [123]. The major mechanism of resistance to tetracycline in Gram-negative bacteria is drug-specific efflux. Drug efflux pumps are involved in fluoroquinolone resistance of Staphylococcus aureus and Streptococcus pneumoniae, and the antiseptic resistance of Staphylococcus aureus. When multidrug pumps are overexpressed, resistance levels are elevated. Efflux pumps are thus potential antibacterial targets, since inhibitors of bacterial efflux pumps may restore the activity of an antibiotic which otherwise is effluxed [124]. Structural knowledge at the atomic level from X-ray crystallographic studies of bacterial multidrug transporters is rapidly growing. Examples are the E. coli EmrD [68], E. coli AcrB [73–78], E. coli EmrE [82, 83], and Staphylococcus aureus Sav1866 [88] crystal structures. 6.3 CNS Drug Targets 6.3.1 Neurotransmitter:Sodium Symporter Family Some of the most successful CNS drugs selectively target secondary transporters. Transporters at the plasma membrane contribute to the clearance

40 A.W. Ravna et al. and recycling of neurotransmitters in neural synaptic clefts. When a neurotransmitter transporter is inhibited, the concentration of neurotransmitter increases in the synapse. The A. aeolicus LeuTAa crystal structure [64] of the NSS family has delivered new insight into the structure of NSS transporters. Its homologies to the human transporters SERT, NET and DAT are 20–25% [64]. The high sequence conservation in functionally important regions between the A. aeolicus LeuTAa transporter and the other NSS family members suggests that these proteins share a common folding and a common transport mechanism, and that the A. aeolicus LeuTAa crystal structure can be used to model the functionally important regions of other NSS family members with quite high accuracy [59]. Serotonin and Noradrenaline Transporters Noradrenaline and 5-HT modulate the activity of neural circuits influencing mood and sleep. Antidepressants selectively inhibit 5-HT or noradrenaline reuptake into presynaptic neurons. Selective serotonin reuptake inhibitors (SSRIs) have replaced tricyclic antidepressants as the drugs of choice in the treatment of depressive disorders, mainly because of their improved tolerability and safety if taken in overdose. Still, 10–30% of patients taking antidepressants are partially or totally resistant to the treatment. SSRIs block the reuptake of serotonin into the presynaptic nerve terminals, thereby enhancing serotonergic neurotransmission, which presumably results in their antidepressant effects. SSRIs are prescribed for conditions such as depression, obsessive-compulsive disorder, social phobia, post-traumatic stress disorder, premenstrual dysphoric disorder and generalized anxiety disorder [125]. Side effects of SSRIs include agitation, insomnia, neuromuscular restlessness, nausea, dry mouth, fatigue, decreased libido, diarrhoea, vomiting and headache. Reboxetine is a specific noradrenaline reuptake inhibitor (NARI). The side effects of NARIs include dry mouth, constipation, insomnia, increased sweating, tachycardia, vertigo, urinary retention and impotence. The general limitations of SSRIs and NARIs are due to side effects directly related to their effect on the serotonergic and noradrenergic systems. Discontinuation symptoms from SSRIs and NARIs are depression, dizziness, nausea, lethargy, headache, flu-like feelings, panic attacks, numbness, agitation and insomnia. A better understanding of the molecular mechanisms of SERT and NET is important for developing new agents with fewer side effects. The molecular aspects of SSRI binding to SERT and NET have been the subject of several molecular modelling studies [126–129]. The A. aeolicus LeuTAa crystal structure [64] represented a major advance towards understanding the structure–function relationships of SERT and NET, since this transporter is quite close both in function and amino acid sequence to human SERT and NET, and thus provides a template for updated models [59, 85, 130, 131]. In order to examine the molecular aspects of the selectivities of SSRIs,

Membrane Transporters: Structure, Function and Targets for Drug Design 41 Fig. 10 Cα trace of the homology model of SERT [131] viewed in the membrane plane. Colour coding as in Fig. 4 we have constructed molecular models of SERT [131] (Fig. 10) and NET based on the A. aeolicus LeuTAa crystal structure [64]. The ICM pocket finder of the ICM software version 3.4–4 [132] reported amino acids in TMHs 1, 3, 6 and 8 of SERT and NET as being contributors to the putative substrate binding area. Dopamine Transporter and Drugs of Abuse Dopamine is involved in the reward system, which is linked to drug abuse. When a person receives positive reinforcement for certain behaviours, which can be both natural rewards and artificial rewards such as addictive drugs, the reward system is activated [133]. When cocaine binds to the dopamine transporter (DAT), the dopamine concentration at the synapse is elevated, resulting in activation of a “reward” mechanism. The binding of cocaine to SERT and NET also contributes to cocaine reward and cocaine aversion [134, 135]. We have previously constructed 3D models of DAT [127–129, 136] based on various low-resolution structural data and transporters with low homology with DAT. The A. aeolicus LeuTAa X-ray crystal structure [64] provides the possibility of updating the previous DAT models. Figure 11 shows a putative binding site of cocaine in DAT (unpublished). Site-directed mutagenesis studies and docking studies of cocaine binding to DAT indicated that cocaine

42 A.W. Ravna et al. Fig. 11 Cocaine docked into the putative binding site of the DAT model. Amino acids interacting with cocaine displayed in the figure are Asp-79, Val-152 and Tyr-156 interacts with Asp-79 [137], Val-152 [138] and Tyr-156. Tyr-156 corresponds to Tyr-176 in SERT, which has been found by site-directed mutagenesis studies to be important for cocaine binding [139]. Interestingly, cocaine and SSRIs have similar molecular mechanisms of action. However, while SSRIs are therapeutic drugs prescribed for the treatment of depression, cocaine is a local anaesthetic drug and a substance of abuse. Knowledge of cocaine’s molecular interactions with DAT may be used to develop agents that block binding of cocaine without inhibiting the reuptake of dopamine. Such agents might be effective in treating cocaine addiction. GABA Transporter The neurotransmitter GABA transmits inhibitory signals that reduce excitation and anxiety. A search for selective inhibitors of GABA transporters has led to potent and selective inhibitors of GAT-1 (SwissProt accession number P30531), which is a 12 TMH transporter with homology to LeuTAa [59]. The only clinically approved GAT-1 inhibitor at present is tiagabine [140, 141]. Tiagabine is a potent and broad spectrum anticonvulsant drug which does not induce tolerance to the anticonvulsant effect [142]. Tiagabine has also shown promise in clinical trials to treat chronic daily headaches with symptoms of migraine [143], and it has been suggested from preclinical studies and human studies that tiagabine also possesses anxiolytic properties [141]. Tiagabine has also been reported to be effective in prophylactic treatment of bipolar disorder [144, 145], but its therapeutic potential in this condition has not been established. A comprehensive amino acid alignment, including the A. aeolicus LeuTAa sequence, sequences of GABA transporters and the sequences of other NSS family members, would provide the possibility of modelling the ligand bind-